CRIS

Permanent URI for this communityhttps://investigadores.udd.cl/handle/123456789/1

Browse

Search Results

Now showing 1 - 10 of 27

Some of the metrics are blocked by your
consent settings
Continuing education course on genetic epilepsies was held by the Chilean society of epileptology
(Wiley, 2026-02-26)
Sebastián Silva‐Soto
;
PEREZ PALMA, EDUARDO ESTEBAN
;
Rikke Møller
;
Maria Roberta Cilio
;
Dennis Lal
1
Some of the metrics are blocked by your
consent settings
Polygenic scores contribution to Parkinson’s disease comorbidities
(Oxford University Press (OUP), 2025)
Carlos F Hernández
;
Camilo Villaman
;
Cristian Tejos
;
REPETTO LISBOA, MARIA GABRIELA
;
Costin Leu
Comorbidities are common in Parkinson’s disease and significantly impact the disease progression and management. While polygenic scores have been widely used to assess genetic risk for complex diseases, their role in comorbidity presentation in Parkinson’s disease remains unclear. This study investigates whether genetic predisposition to comorbidities, as measured by polygenic scores, differs between individuals with Parkinson’s disease and the general population and explores how genetic risk influences disease onset and sex-related differences. We analysed data from 4144 individuals with Parkinson’s disease and 370 480 individuals from the general population in the UK Biobank, focusing on four comorbidities with high-quality genome-wide association study data: Type 2 diabetes, major depressive disorder, migraine headaches and epilepsy. We first compared polygenic score distributions between individuals with Parkinson’s disease and the general population. While our findings indicate that comorbidities and polygenic risk scores do not significantly differ between individuals with Parkinson’s disease and the general population, we show an association with disease onset and sex-specific differences. Individuals with earlier disease onset (50–70 years old) had higher genetic risk for major depressive disorder (odds ratio: 2.19, P-value: 1.27 × 10⁻¹⁵) and epilepsy (odds ratio: 1.58, P-value: 0.00845). Additionally, a female participant with Parkinson’s disease exhibited higher genetic risk scores for major depressive disorder (odds ratio: 1.5, P-value: 0.0119) and migraine headaches (odds ratio: 2.1, P-value: 0.0155), while a male participant displayed higher genetic risk scores for Type 2 diabetes (odds ratio: 2.7, P-value: 2.11 × 10⁻¹⁷). Comorbidity-polygenic score did not differ between people with versus without Parkinson’s disease, yet within Parkinson’s disease, a higher genetic burden for specific comorbidities was linked to earlier onset and sex-specific presentation, implicating common variants as modifiers of clinical heterogeneity rather than the primary disease risk. These results enhance our understanding of the genetic influences shaping the broader clinical presentation of Parkinson’s disease and highlight the need for further research into the interplay between genetic risk factors, comorbidities and disease heterogeneity.
Scopus© Citations 2 3
Some of the metrics are blocked by your
consent settings
Conserved missense variant pathogenicity and correlated phenotypes across paralogous genes
(Springer Science and Business Media LLC, 2025-07-07)
Tobias Brünger
;
Alina Ivaniuk
;
PEREZ PALMA, EDUARDO ESTEBAN
;
Ludovica Montanucci
;
Stacey Cohen
The majority of missense variants in clinical genetic tests are classified as variants of uncertain significance. Prior research shows that the deleterious effects and the subsequent molecular consequences of variants are often conserved among paralogous protein sequences within a gene family. Here, we systematically quantify on an exome-wide scale whether the existence of pathogenic variants in paralogous genes at a conserved position can serve as evidence for the pathogenicity of a new variant. For the gene family of voltage-gated sodium channels, where variants and expert-curated clinical phenotypes are available, we also assess whether phenotype patterns of multiple disorders for each gene are conserved across variant positions within the gene family.</jats:p> Mapping 590,000 pathogenic and 1.9 million population variants onto 9928 genes grouped into 2054 paralogous families increases the number of residues with classifiable evidence 5.1-fold compared with gene-specific data alone. The presence of a pathogenic variant in a paralogous gene is associated with a positive likelihood ratio of 13.0 for variant pathogenicity. Across ten genes encoding voltage-gated sodium channels and 22 expert-curated disorders, we identify cross-paralog correlated phenotypes based on 3D structure spatial position. For example, multiple established loss-of-function related disorders across SCN1A, SCN2A, SCN5A, and SCN8A show overlapping spatial variant clusters. Finally, we show that phenotype integration in paralog variant selection improves variant classification.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusion</jats:title> <jats:p>Conserved pathogenic missense variants in paralogous genes provide robust, quantifiable support for clinical variant interpretation, and phenotype-informed mapping further improves predictions.</jats:p> </jats:sec>
1
Some of the metrics are blocked by your
consent settings
SCN9A should not be considered an epilepsy gene; Refuting a gene-disease association
(Wiley, 2025-06-10)
Ismael Ghanty
;
PEREZ PALMA, EDUARDO ESTEBAN
;
Camilo Villaman
;
Daniel Stobo
;
Joseph Symonds
Objective The SCN9A gene is primarily expressed in nociceptive pathways within the peripheral nervous system, and pathogenic variants are associated with human pain disorders. In recent years, several studies have proposed SCN9A as a monogenic cause of epilepsy. Our objective was to critically appraise the SCN9A–epilepsy gene–disease relationship. Methods We assessed “epilepsy-associated” SCN9A variants from four sources: (1) the literature up to December 2023 (n = 27), (2) epilepsy patients referred for genetic testing at a regional service in Glasgow, UK over a 5-year period (n = 30), (3) the Human Genetics Mutation Database (n = 25), and (4) ClinVar (n = 1546). The latter two are genome-wide variant databases, accepting submissions from genetic laboratories and research groups. We checked whether each SCN9A variant is present in the Genome Aggregation Database (gnomAD) V4 (a reference population database for variant interpretation), and classified its pathogenicity based on the American College of Molecular Genetics and Genomics/Association of Molecular Pathologists guidelines. Results Only three SCN9A variants were classified as “likely pathogenic,” of which two were identified in healthy individuals in gnomAD. A total of 1540 of the 1546 SCN9A variants in ClinVar labeled as being associated with epilepsy were also reported in association with hereditary sensory and autonomic neuropathy. No further clinical data were provided in 1482 of these submissions. Significance There is no convincing genetic evidence to support SCN9A as a causative epilepsy gene. As such, the inclusion of SCN9A in epilepsy genetic testing panels should be reassessed. Research centers and genetic testing laboratories should be rigorous and consistent in their submissions to variant databases.
Scopus© Citations 3 4
Some of the metrics are blocked by your
consent settings
Polygenic score analysis identifies distinct genetic risk profiles in Alzheimer’s disease comorbidities
(Springer Science and Business Media LLC, 2025-04-03)
Carlos F. Hernández
;
Camilo Villaman
;
Costin Leu
;
Dennis Lal
;
Ignacio Mata
4
Some of the metrics are blocked by your
consent settings
Evaluating novel in silico tools for accurate pathogenicity classification in epilepsy‐associated genetic missense variants
(2024)
Ludovica Montanucci
;
Tobias Brünger
;
Christian M. Boßelmann
;
Alina Ivaniuk
;
Eduardo Pérez‐Palma
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>Determining the pathogenicity of missense variants in clinical genetic tests for individuals with epilepsy is crucial for guiding personalized treatment. However, achieving a definitive pathogenic classification remains challenging, with most missense variants still classified as variants of uncertain significance (VUS) and with the availability of many computational tools which may provide conflicting predictions. Here, we aim to evaluate the performance of state‐of‐the‐art computational tools in pathogenicity prediction of missense variants in epilepsy‐associated genes. This will assist in selecting the most appropriate tool and critically assess their use in clinical setting.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We assessed the performance of nine in silico pathogenicity prediction tools for missense variants in epilepsy‐associated genes on three carefully curated data sets. The first two data sets comprise missense variants in epilepsy associated genes that have been uploaded to ClinVar in the last year and were, therefore, not part of the training set of any of the nine considered tools. These two data sets are based on two different lists of epilepsy‐associated genes and comprise ~700 and ~ 250 missense variants, respectively. The third data set includes ~400 missense variants within epilepsy‐associated genes for which the functional effects have been determined experimentally and are therefore used here to infer pathogenicity. These three data sets represent the best available approximation to blind and independent test sets.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Among the nine assessed tools, AlphaMissense (area under the curve [AUC]: .93, .88, and .95) and REVEL (AUC: .93, .88, and .93) showed the best classification performance, also outperforming other tools in the number of classified variants.</jats:p></jats:sec><jats:sec><jats:title>Significance</jats:title><jats:p>We show which recently developed prediction tools achieve higher performance in epilepsy‐associated genes and should be integrated, therefore, into the American College of Medical Genetics and Genomics/Association of Molecular Pathology (AGMC/AMP) variant classification process. Periodic reevaluation of genetic test results with newly developed or updated tools should be incorporated into standard clinical practice to improve diagnostic yield and better inform precision medicine.</jats:p></jats:sec>
Scopus© Citations 2
Some of the metrics are blocked by your
consent settings
Genotype–phenotype associations in 1018 individuals with <i>SCN1A</i>‐related epilepsies
(2024)
Declan Gallagher
;
Eduardo Pérez‐Palma
;
Tobias Bruenger
;
Ismael Ghanty
;
Eva Brilstra
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p><jats:italic>SCN1A</jats:italic> variants are associated with epilepsy syndromes ranging from mild genetic epilepsy with febrile seizures plus (GEFS+) to severe Dravet syndrome (DS). Many variants are de novo, making early phenotype prediction difficult, and genotype–phenotype associations remain poorly understood.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We assessed data from a retrospective cohort of 1018 individuals with <jats:italic>SCN1A‐</jats:italic>related epilepsies. We explored relationships between variant characteristics (position, in silico prediction scores: Combined Annotation Dependent Depletion (CADD), Rare Exome Variant Ensemble Learner (REVEL), <jats:italic>SCN1A</jats:italic> genetic score), seizure characteristics, and epilepsy phenotype.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>DS had earlier seizure onset than other GEFS+ phenotypes (5.3 vs. 12.0 months, <jats:italic>p</jats:italic> < .001). In silico variant scores were higher in DS versus GEFS+ (<jats:italic>p</jats:italic> < .001). Patients with missense variants in functionally important regions (conserved N‐terminus, S4–S6) exhibited earlier seizure onset (6.0 vs. 7.0 months, <jats:italic>p</jats:italic> = .003) and were more likely to have DS (280/340); those with missense variants in nonconserved regions had later onset (10.0 vs. 7.0 months, <jats:italic>p</jats:italic> = .036) and were more likely to have GEFS+ (15/29, χ<jats:sup>2</jats:sup> = 19.16, <jats:italic>p</jats:italic> < .001). A minority of protein‐truncating variants were associated with GEFS+ (10/393) and more likely to be located in the proximal first and last exon coding regions than elsewhere in the gene (9.7% vs. 1.0%, <jats:italic>p</jats:italic> < .001). Carriers of the same missense variant exhibited less variability in age at seizure onset compared with carriers of different missense variants for both DS (1.9 vs. 2.9 months, <jats:italic>p</jats:italic> = .001) and GEFS+ (8.0 vs. 11.0 months, <jats:italic>p</jats:italic> = .043). Status epilepticus as presenting seizure type is a highly specific (95.2%) but nonsensitive (32.7%) feature of DS.</jats:p></jats:sec><jats:sec><jats:title>Significance</jats:title><jats:p>Understanding genotype–phenotype associations in <jats:italic>SCN1A</jats:italic>‐related epilepsies is critical for early diagnosis and management. We demonstrate an earlier disease onset in patients with missense variants in important functional regions, the occurrence of GEFS+ truncating variants, and the value of in silico prediction scores. Status epilepticus as initial seizure type is a highly specific, but not sensitive, early feature of DS.</jats:p></jats:sec>
1Scopus© Citations 30
Some of the metrics are blocked by your
consent settings
Molecular dynamics simulations reveal molecular mechanisms for the gain and loss of function effects of four SCN2A variants
(2024)
PEREZ PALMA, EDUARDO ESTEBAN
;
Nisha Bhattarai
;
Ludovica Montanucci
;
Bruenger, Tobias
;
Martin, William
3
Some of the metrics are blocked by your
consent settings
Genomic analysis of AlphaFold2-predicted structures identifies maps of 3D essential sites in 243 neurodevelopmental disorder-associated proteins
(2022)
Sumaiya Iqbal
;
Tobias Brünger
;
Eduardo Pérez-Palma
;
David Hoksza
;
Arthur J. Campbell
14
Some of the metrics are blocked by your
consent settings
GRIN Portal: An Interactive Web Application Exploring GRIN Genes and Related Disorders
(2023)
PEREZ PALMA, EDUARDO ESTEBAN
;
Kloeckner, Chiara
;
Bruenger, Tobias
;
Krey, Ilona
;
Macnee, Marie
1

CRIS

Browse

Filters

Settings

Sort By

Results per page

Search Results